Abstract

A key challenge for grid computing is creating large-scale, end-to-end scientific applications that draw from pools of specialized scientific components to derive elaborate new results. We develop Pegasus, an AI planning system which is integrated into the grid environment that takes a user's highly specified desired results, generates valid workflows that take into account available resources, and submits the workflows for execution on the grid. We also begin to extend it as a more distributed and knowledge-rich architecture.

Metadata

publication

IEEE Intelligent Systems 19 (1), 26-33, 2004

year

2004

publication date

2004/1

authors

Yolanda Gil, Ewa Deelman, Jim Blythe, Carl Kesselman, Hongsuda Tangmunarunkit

link

https://ieeexplore.ieee.org/abstract/document/1265882/

resource_link

https://scitech.isi.edu/wordpress/wp-content/papercite-data/pdf/gil2004ai.pdf

journal

IEEE Intelligent Systems

volume

19

issue

1

pages

26-33

publisher

IEEE